Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Antonio Benítez-Hidalgo"'
Autor:
Antonio Benítez-Hidalgo, José F. Aldana-Montes, Ismael Navas-Delgado, María del Mar Roldán-García
Publikováno v:
BMC Bioinformatics, Vol 24, Iss 1, Pp 1-18 (2023)
Abstract Background Information provided by high-throughput sequencing platforms allows the collection of content-rich data about biological sequences and their context. Sequence alignment is a bioinformatics approach to identifying regions of simila
Externí odkaz:
https://doaj.org/article/fcbdef2ee39a4f4e8dfac0c82a579161
Autor:
Antonio J. Nebro, Antonio Benítez-Hidalgo, José García-Nieto, José F. Aldana-Montes, Cristóbal Barba-González
Publikováno v:
idUS. Depósito de Investigación de la Universidad de Sevilla
instname
idUS: Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
instname
idUS: Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
A number of streaming technologies have appeared in the last years as a result of the rising of Big Data applications. Nowadays, deciding which technology to adopt is not an easy task due not only to the number of available data streaming processing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16b7d209a4970a9747d8c2b66f9efe9f
Publikováno v:
Bioinformatics. 36:3892-3893
Motivation Multiple sequence alignment (MSA) consists of finding the optimal alignment of three or more biological sequences to identify highly conserved regions that may be the result of similarities and relationships between the sequences. MSA is a
Publikováno v:
idUS: Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
BIRD: BCAM's Institutional Repository Data
instname
idUS. Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
BIRD: BCAM's Institutional Repository Data
instname
idUS. Depósito de Investigación de la Universidad de Sevilla
This paper describes jMetalPy, an object-oriented Python-based framework for multi-objective optimization with metaheuristic techniques. Building upon our experiences with the well-known jMetal framework, we have developed a new multi-objective optim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::517eae2f70aef8bdd3e383d8e37dcbff
Autor:
José García-Nieto, Antonio Benítez-Hidalgo, Carlos A. Coello Coello, Juan J. Durillo, Javier Del Ser, Cristóbal Barba-González, Antonio J. Nebro, José F. Aldana-Montes
Publikováno v:
Parallel Problem Solving from Nature – PPSN XV ISBN: 9783319992525
PPSN (1)
PPSN (1)
The Speed-constrained Multi-objective PSO (SMPSO) is an approach featuring an external bounded archive to store non-dominated solutions found during the search and out of which leaders that guide the particles are chosen. Here, we introduce SMPSO/RP,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::914dd968d577c9fd60d32d547a4efbc1
https://doi.org/10.1007/978-3-319-99253-2_24
https://doi.org/10.1007/978-3-319-99253-2_24
Autor:
Antonio J. Nebro, Esteban López-Camacho, José F. Aldana-Montes, Juan J. Durillo, José García-Nieto, Cristóbal Barba-González, Antonio Benítez-Hidalgo
Publikováno v:
Intelligent Distributed Computing XII ISBN: 9783319996257
IDC
idUS: Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
RIUMA. Repositorio Institucional de la Universidad de Málaga
instname
idUS. Depósito de Investigación de la Universidad de Sevilla
IDC
idUS: Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
RIUMA. Repositorio Institucional de la Universidad de Málaga
instname
idUS. Depósito de Investigación de la Universidad de Sevilla
Multi-objective optimization with metaheuristics is an active and popular research field which is supported by the availability of software frameworks providing algorithms, benchmark problems, quality indicators and other related components. Most of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6d22c49bd70a3784317f162ad094a211
Autor:
José García-Nieto, Cristóbal Barba-González, José F. Aldana-Montes, Antonio Benítez-Hidalgo, Antonio J. Nebro
Publikováno v:
Intelligent Distributed Computing XII ISBN: 9783319996257
IDC
IDC
Inference of Gene Regulatory Networks (GRNs) remains an important open challenge in computational biology. The goal of bio-model inference is to, based on time-series of gene expression data, obtain the sparse topological structure and the parameters
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e405b041bfcc25d93201f4f583912b2
https://doi.org/10.1007/978-3-319-99626-4_6
https://doi.org/10.1007/978-3-319-99626-4_6